GenAI Data Solutions Engineer - Forward-Deployed

United States Digital Space LLC; United States; Remote; USD 150,000 - 200,000; Full time

Benefits offered by this job

Medical insurance

Dental insurance

Vision coverage

Retirement plan

Paid time off

Job summary

United States Digital Space LLC is seeking a Forward Deployed Engineer to work with enterprise clients to design, deploy, and optimise GenAI data solutions, owning data quality and delivery readiness across engineering and operations.

You will build scalable validation and automation pipelines, define requirements, shape annotation guidelines, and ensure datasets meet acceptance criteria, with a focus on reliability and observability in a fast-moving AI environment.

Qualifications

• Experience with GenAI, machine learning, or model evaluation data.
• A consultative problem-solving approach when leading client conversations, asking sharp questions, guiding stakeholders toward better decisions.
• Hands-on experience designing and implementing data pipelines, validation systems, or workflow automation.
• Previous experience owning final data quality and delivering readiness.
• Ability to translate business or model development needs into technical workflows and validation logic.

Responsibilities

• Define requirements, success criteria, and high-quality annotation guidelines with clients.
• Translate ambiguous client needs into clear, scalable GenAI data workflows.
• Deliver zero-defect GenAI datasets that meet acceptance and quality criteria.
• Build scalable, reproducible validation and automation pipelines to reduce variance and rework.
• Contribute reusable quality frameworks and validators across projects.

Skills

GenAI data

Data pipelines

Validation systems

Client consulting

Tools

Workflow automation

Job description

United States Digital Space LLC is seeking a Forward Deployed Engineer to work with enterprise clients to design, deploy, and optimise GenAI data solutions, owning data quality and delivery readiness across engineering and operations.

You will build scalable validation and automation pipelines, define requirements, shape annotation guidelines, and ensure datasets meet acceptance criteria, with a focus on reliability and observability in a fast-moving AI environment.